The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 11, 2026

Filed:

Jan. 29, 2024
Applicant:

Salesforce, Inc., San Francisco, CA (US);

Inventors:

Akash Gokul, San Francisco, CA (US);

Nikhil Naik, Mountain View, CA (US);

Senthil Purushwalkam Shiva Prakash, Mountain View, CA (US);

Assignee:

Salesforce, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 11/00 (2026.01); G06V 10/77 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06T 11/00 (2013.01); G06V 10/7715 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01);
Abstract

Embodiments described herein provide a framework designed to enable personalized image generation capabilities in a pretrained text-to-image generation model. The architecture comprises two replicas of the pretrained text-to-image model—a reference UNet dedicated to extracting visual features from reference images and a base UNet for the actual image generation process. The reference UNet processes reference images to collect the features before each Self-Attention (SA) layer of the reference UNet. The base UNet's SA layers are modified to 'Reference Self-Attention' (RSA) layers that allow conditioning on extra features. Using the collected reference features as input, the base UNet equipped with the RSA layers estimates the noise in the input to guide the image generation towards the reference objects.


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